Distributed trust management scheme based on blockchain in Internet of vehicles by Haibo ZHANG, Yukun CAO, Kaijian LIU, Ruyan WANG

“…Aiming at the security problems caused by the low efficiency and accuracy of malicious vehicle identification in Internet of vehicles, a distributed trust management scheme based on blockchain in Internet of vehicles was proposed.A false information identification strategy was designed by aggregating the scoring information of vehicles, combined with Bayesian inference model.A reputation value updating algorithm was designed by combining the historical interaction information of vehicles and traffic information, malicious vehicles were identified by the reputation threshold.A blockchain was constructed roadside units to realize the distributed storage of traffic data and vehicle reputation values.The traditional proof of work consensus mechanism was improved to dynamically change the difficulty of miner node generating a block through the event level and the number of vehicles involved in scoring, and the waiting mechanism was used to temporarily stop the nodes that had recently blocked from participating in the election process of miner nodes, thus reducing the resource consumption caused by repeated calculations.The simulation results show that the proposed scheme can effectively identify false information, resist the deceptive behavior of malicious vehicles, improve the identification efficiency of malicious vehicles, reduce resource consumption, and is effective and feasible in distributed trust management for Internet of vehicles.…”
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A New Contact Force Estimation Method for Heavy Robots Without Force Sensors by Combining CNN-GRU and Force Transformation by Peizhang Wu, Hui Dong, Pengfei Li, Yifei Bao, Wei Dong, Lining Sun

“…This method can achieve robot end contact force estimation without a force sensor, avoiding the cumbersome manual modeling and identification process. Compared with traditional manual modeling and identification methods, experiments show that the proposed method in this paper can approximately double the estimation accuracy of the contact force of heavy robots and reduce the time consumption by approximately half, with advantages such as convenience, efficiency, strong real-time performance, and high accuracy.…”
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CONCEPTION OF USE VIBROACOUSTIC SIGNALS AND NEURAL NETWORKS FOR DIAGNOSING OF CHOSEN ELEMENTS OF INTERNAL COMBUSTION ENGINES IN CAR VEHICLES by Piotr CZECH

“…Currently used diagnostics systems are not always efficient and do not give straightforward results which allow for the assessment of the technological condition of the engine or for the identification of the possible damages in their early stages of development. …”
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Classification of microscopic images of rock thin sections based on TLCA-ResNet34 by Zhenyu Zhao, Shucheng Tan, Hui Chen, Pengwei Wang, Qinghua Zhang, Haoyu Wei, Zhenlin Zhang

“…By adopting the transfer learning method, a context-aware residual block was designed using the coordinate attention(CA) mechanism, and a targeted TLCA-ResNet34 neural network model was developed. This model is capable of extracting deep-layer feature information from entire rock thin section images, thus achieving the classification and identification of microscopic images. …”
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Machine-Learning-Guided Design of Nanostructured Metal Oxide Photoanodes for Photoelectrochemical Water Splitting: From Material Discovery to Performance Optimization by Xiongwei Liang, Shaopeng Yu, Bo Meng, Yongfu Ju, Shuai Wang, Yingning Wang

“…We then discuss the integration of ML techniques—ranging from high-throughput density functional theory (DFT)-based screening to experimental data-driven modeling—for accelerating the identification of promising oxides (e.g., BiVO₄, Fe₂O₃, WO₃) and optimizing key parameters such as dopant selection, morphology, and catalyst interfaces. …”
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Intelligent back-to-back testing with denoising autoencoder-based fault detection and DBSCAN clustering by Mohammad Abboush, Christoph Knieke, Andreas Rausch

“…Back-to-back (B2B) test has been introduced as a pivotal method for ensuring equivalence between model-level and implementation-level behaviour during the validation process of Automotive Software Systems (ASSs). …”
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Tightly Coupling Fusion of UWB Ranging and IMU Pedestrian Dead Reckoning for Indoor Localization by Rashid Ali, Ran Liu, Anand Nayyar, Basit Qureshi, Zhiqiang Cao

“…Moreover, we consider the UWB NLOS and IMU error identification. A real-time ranging error compensation model based on the LS method and AKF positioning algorithm are used for fixing such problems. …”
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Machine learning algorithm for the rapid and accurate detection of Plasmodium falciparum by Mr Andrew Hill

“…Conclusion: Accurate Plasmodium falciparum parasite identification is possible with 12,000 parameter models. …”
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Ship Contour: A Novel Ship Instance Segmentation Method Using Deep Snake and Attention Mechanism by Chen Chen, Songtao Hu, Feng Ma, Jie Sun, Tao Lu, Bing Wu

“…These improvements to CenterNet enhance model robustness and effectively reduce missed and false detection. …”
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Analysis of Corn Deterioration Due to Molding Using Surface-Enhanced Raman Spectroscopy by Xiaoyan Wei, Guifang Wu, Pengcheng Qiu, Huihe Yang, Shubin Yan, Jianing Di, Xiangpeng Zhao, Feixu Zhang, Hongda Zhang

“…Efficient and rapid identification of corn mildew levels is essential for proper storage and transportation. …”
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Chaperone overexpression boosts heterologous small molecule production in Saccharomyces cerevisiae by Andreas M Vestergaard, Wasti Nurani, Paul Cachera, Uffe H Mortensen

“…Conclusion The endogenous cytosolic chaperone overexpression library and mating based screening method presented in this report constitute a tool allowing for fast and efficient identification of specific chaperones and chaperone combinations that benefit production of a given SM in S. cerevisiae-based cell factories.…”
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Research on the connectivity reliability analysis and optimization of natural gas pipeline network based on topology by Xiuxuan Yang, Kun Chen, Minghui Liu

“…First, a minimum path set-based reliability model is developed, leveraging an enhanced depth-first search (DFS) algorithm for efficient path identification and binary decision diagrams (BDD) to eliminate 92% of redundant terms in reliability formulas, reducing computational complexity by 40% compared to Monte Carlo simulations. …”
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SPHERE: Benchmarking YOLO vs. CNN on a Novel Dataset for High-Accuracy Solar Panel Defect Detection in Renewable Energy Systems by Kubilay Ayturan, Berat Sarıkamış, Mehmet Feyzi Akşahin, Uğurhan Kutbay

“…Pre-trained models (e.g., VGG16 and ResNet) were assessed but outperformed by YOLO variants. …”
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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…Rolling Element Bearings perform a vital function by ensuring the reliable and efficient operation of machinery in modern industries. …”
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A Novel Authentication Management for the Data Security of Smart Grid by Imtiaz Parvez, Maryamossadat Aghili, Hugo Riggs, Aditya Sundararajan, Arif I. Sarwat, Anurag K. Srivastava

“…Recognizing this, this study presents a novel authentication management (model) comprised of two layer security schema. The first layer implements an efficient novel encryption method for secure data exchange between meters and control center with the help of two partially trusted simple servers (constitutes the TTP). …”
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Detection of fractured zones, faults, and cavities by high resolution muon tomography in the Buda Hills by László Balázs, Gergő Hamar, Ádám Csicsek, Gergely Surányi, Dezső Varga

“…In this paper we present a muography based high precision identification of a fractured zones and cavities which explorations are challenging to surface geophysical methods. …”
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Quantum proof biometric authentication framework using binary lattices and homomorphic encryption for secure cancelable templates by S. Aarthi, K. Geetha, N. Sasikaladevi

“…The AEGIIS scheme was designed to operate on the Ring-Learning-with-Errors hardness problem, which exhibits the super polynomial complexity of $$\ {O(n \log n)}$$ O ( n log n ) and is resilient to both classical and quantum attacks and tested using indistinguishability analysis through IND-CPA analysis on ROM model, achieving post-quantum security with a key size of 256 bits.…”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Secondly, we design a two-tier stacked ensemble architecture, which not only combines the strengths of multiple machine learning algorithms, e.g., gradient-boosted decision tree (GBDT), random forest (RF), and extreme gradient boosting (XGBoost), with deep learning models, e.g., gated recurrent unit (GRU) and long short-term memory (LSTM), but also implements the support vector machine (SVM) for efficient meta-learning. …”
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Improving Moving Insect Detection with Difference of Features Maps in YOLO Architecture by Angel Gomez-Canales, Javier Gomez-Avila, Jesus Hernandez-Barragan, Carlos Lopez-Franco, Carlos Villaseñor, Nancy Arana-Daniel

“…Insect detection under real-field conditions remains a challenging task due to factors such as lighting variations and the small size of insects that often lack sufficient visual features for reliable identification by deep learning models. These limitations become especially pronounced in lightweight architectures, which, although efficient, struggle to capture fine-grained details under suboptimal conditions, such as variable lighting conditions, shadows, small object size and occlusion. …”
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A Fast Recognition Method for Space Targets in ISAR Images Based on Local and Global Structural Fusion Features with Lower Dimensions by Hong Yang, Yasheng Zhang, Wenzhe Ding

“…The proposed method provides a fast and effective high-precision model for space target feature extraction, which can give some references for solving the problem of space object efficient identification under the condition of small sample data.…”
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